LCR-modules: reproducible workflows to analyze massive genomic datasets

LCR-modules is a collection of standard analytical modules for genomic and transcriptomic data. Too often do we copy-paste from each other’s pipelines, which has several pitfalls. Fortunately, all of these problems can be solved with standardized analytical modules, and the benefits are many.

The exponential growth in genomic data from advanced sequencing technologies requires avialability of efficient, scalable, and reproducible bioinformatics pipelines. As part of Lymphoid Cancer Research Department team at the BC Cancer, I contributed to the development of the Lymphoid Cancer Research modules (LCR-modules), a suite of open-source bioinformatics tools designed to leverage diverse genomic data types, including whole genome, exome, and long-read sequencing. Built on the Snakemake workflow management system, LCR-modules offers a versatile toolkit for processing and analyzing large genomic datasets. The suite comprises 49 workflows organized into three levels, facilitating tasks from low-level quality control to complex cohort-level analyses. LCR-modules supports various sequencing types and integrates features like mutation calling, gene expression analysis, and data aggregation, ensuring flexibility and reproducibility. Available at https://github.com/LCR-BCCRC/lcr-modules, LCR-modules represents a significant advancement in genomic data analysis, addressing key challenges in reproducibility and scalability.

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